Example: Population Standard Deviation.

Grandma Hinkle has four grown sons with heights of 170, 173, 174, and 180 cm. Find the population standard deviation of their heights.

Keys:

Display:Description:

{c{´}

170 173 

174 180 

{σº}





) UºU¸σºσ¸

) 

Clears the statistics registers. Enters data. Four data points accumulated.

Calculates the population standard deviation.

Linear Regression

Linear regression, L.R. (also called linear estimation) is a statistical method for finding a straight line that best fits a set of x,y–data.

Note

To avoid a !!  message, enter your data before executing any of the functions in the L.R. menu.

 

L.R. (Linear Regression) Menu

 

 

Menu Key

Description

 

 

{ ˆ }

Estimates (predicts) x for a given hypothetical value of y,

º

based on the line calculated to fit the data.

 

{ ˆ }

Estimates (predicts) y for a given hypothetical value of x,

¸

based on the line calculated to fit the data.

 

{T}

Correlation coefficient for the (x, y) data. The correlation

 

coefficient is a number in the range –1 through +1 that

 

measures how closely the calculated line fits the data.

{P}

Slope of the calculated line.

{E}

y–intercept of the calculated line.

 

 

Statistical Operations 11–7